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The DRH is a quantitative and qualitative encyclopedia of religious history. It consists of a variety of entry types including religious group and religious place. Scholars contribute entries on their area of expertise by answering questions in standardised polls. Answers are initially coded in the binary format Yes/No or categorically, with comment boxes for qualitative comments, references and links. Experts are able to answer both Yes and No to the same question, enabling nuanced answers for specific circumstances. Media, such as photos, can also be attached to either individual questions or whole entries. The DRH captures scholarly disagreement, through fine-grained records and multiple temporally and spatially overlapping entries. Users can visualise changes in answers to questions over time and the extent of scholarly consensus or disagreement.
By stimulating inspiring research and producing innovative tools, Huygens ING intends to open up old and inaccessible sources, and to understand them better. Huygens ING’s focus is on Digital Humanities, History, History of Science, and Textual Scholarship. Huygens ING pursues research in the fields of History, Literary Studies, the History of Science and Digital Humanities. Huygens ING aims to publish digital sources and data responsibly and with care. Innovative tools are made as widely available as possible. We strive to share the available knowledge at the institute with both academic peers and the wider public.
The Répertoire International des Sources Musicales (RISM) - International Inventory of Musical Sources - is an international, non-profit organization that aims to comprehensively document extant musical sources worldwide. These primary sources are music manuscripts or printed music editions, writings on music theory, and libretti. They are preserved in libraries, archives, churches, schools and private collections. RISM was founded in Paris in 1952 and is the largest and only international organization that documents written musical sources. RISM records what exists and where it can be found. As a result, by virtue of being cataloged in a comprehensive inventory, music traditions are protected while also being made available to musicologists and musicians alike. Such work is thus not an end in itself, but leads directly to practical applications.
The Alaska Native Language Archive houses documentation of the various Native languages of Alaska and helps to preserve and cultivate this unique heritage for future generations. As the premier repository worldwide for information relating to the Native languages of Alaska, the Archive serves researchers, teachers and students, as well as members of the broader community. The collection includes both published and unpublished materials in or on all of the Alaska Native languages and related languages. The collection has enduring cultural, historic, and intellectual value, particularly for Alaska Native language speakers and their descendants
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Attention! Data sets are not updated anymore. Please, visit the BonaRes Repositor​ium​ for new datasets. Open Research Data provides quality assessed data and their metadata such as context information on measurement objectives, equipment, methods, testing and investigation areas. The purpose of the repository is to secure quality, integrity and long-term availability of landscape and ecosystem research data as well as to enhance accessibility of free data from ZALF long-term monitoring campaigns, landscape laboratories (Agro-ScapeLabs), field trials and experiments. The Leibniz Centre for Agricultural Landscape Research (ZALF) explores ecosystems in agricultural landscapes and the development of ecologically and economically viable land use systems. ZALF combines scientific expertise from agricultural science, geosciences, biosciences and socio-economics.
The OFA databases are core to the organization’s objective of establishing control programs to lower the incidence of inherited disease. Responsible breeders have an inherent responsibility to breed healthy dogs. The OFA databases serve all breeds of dogs and cats, and provide breeders a means to respond to the challenge of improving the genetic health of their breed through better breeding practices. The testing methodology and the criteria for evaluating the test results for each database were independently established by veterinary scientists from their respective specialty areas, and the standards used are generally accepted throughout the world.
The African Development Bank Group (AfDB) is committed to supporting statistical development in Africa as a sound basis for designing and managing effective development policies for reducing poverty on the continent. Reliable and timely data is critical to setting goals and targets as well as evaluating project impact. Reliable data constitutes the single most convincing way of getting the people involved in what their leaders and institutions are doing. It also helps them to get involved in the development process, thus giving them a sense of ownership of the entire development process. The AfDB has a large team of researchers who focus on the production of statistical data on economic and social situations. The data produced by the institution’s statistics department constitutes the background information in the Bank’s flagship development publications. Besides its own publication, the AfDB also finances studies in collaboration with its partners. The Statistics Department aims to stand as the primary source of relevant, reliable and timely data on African development processes, starting with the data generated from its current management of the Africa component of the International Comparison Program (ICP-Africa). The Department discharges its responsibilities through two divisions: The Economic and Social Statistics Division (ESTA1); The Statistical Capacity Building Division (ESTA2)
The Preclinical Image DAtaset Repository (PIDAR) is a public repository of metadata information of preclinical image datasets from any imaging modality associated to peer-review publications. The metadata information are organized in a proper schema to create a standard metadata model for preclinical imaging.